面向分布式电源并网的多谐波源责任划分

Contribution Determination of Multiple Harmonic Sources for Distributed Generations Connected to Grid

充分考虑大量分布式电源接入电网导致背景谐波波动增大以及分布呈非对称特点的影响,提出了一种聚类算法与复合分位数回归相结合的多谐波源责任划分方法。首先,提出基于回归模型系数波动的有效数据选择方法对数据进行处理,在此基础上,采用主导波动量与OFMMK-means聚类算法结合的方法对波动的背景谐波电压进行聚类,并按照电压值分成不同的数据段。其次,采用复合分位数计算每个数据段的谐波责任,进而加权获得总谐波责任。最后,通过实测数据与仿真分析的对比验证结论的正确性。结果表明,所提方法较传统方法有较高的计算精度,且在背景谐波波动大的情况下依旧可以保持良好的准确性和适用性。

Considering the influences of a large number of distributed generations(DGs)connected to grid such as the increasing fluctuations in background harmonics and asymmetrical distribution characteristics,a contribution determi⁃nation method for multiple harmonic sources is proposed by combining the clustering algorithm with composite quantile regression.First,the effective data selection method based on fluctuations in the regression model coefficient is pro⁃posed to process data.On this basis,the fluctuating background harmonic voltage is clustered by combining the domi⁃nant fluctuation with the OFMMK-means clustering algorithm,which is further divided into different data segments.Second,the harmonic contribution of each data segment is calculated by means of the composite quantile,and the total harmonic contribution is obtained through weighting.Finally,the conclusions are verified through the comparison be⁃tween measured data and simulation analysis.Results show that the proposed method has a higher calculation accuracy than the traditional method,and it can maintain a satisfying accuracy and applicability in the case of large fluctuations in background harmonics.